Automated identification and measurement of objects via populations of medial primitives, with application to real time 3D echocardiography

Abstract

We suggest that identification and measurement of objects in 3D images can be automatic, rapid and stable, based on the statistical properties of populations of medial primitives sought throughout the image space. These properties include scale, orientation, endness, and medial dimensionality. The property of medial dimensionality differentiates the sphere, the cylinder, and the slab, with intermediate dimensionality also possible. Endness results at the cap of a cylinder or the edge of a slab. The values of these medial properties at just a few locations provide an intuitive and robust model for complex shape. For example, the left ventricle during systole can be described as a large cylinder with an apical cap at one end, a slab-like mitral valve at the other (closed during systole), and appropriate interrelations among components in terms of their scale, orientation, and location. We demonstrate our method on simple geometric test objects, and show it capable of automatically identifying the left ventricle and measuring its volume in vivo using Real-Time 3D echocardiography.